Method and device for jointly predicting hydrate saturation based on two parameters and equivalent medium

Abstract

The invention discloses a method and a device for jointly predicting hydrate saturation based on two parameters and an equivalent medium. The method comprises the following steps: acquiring deep resistivity and interval transit time data of a target hydrate reservoir area; taking the deep resistivity and interval transit time data as input parameters of a two-parameter model to obtain a hydrate saturation predicted value of the two-parameter model; utilizing the equivalent medium model to calculate a hydrate saturation prediction value of the equivalent medium model; and performing weighted average on the two-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value to obtain a final hydrate saturation prediction value. According to the method, the two-parameter model and the equivalent medium model are combined, so that the physical characteristics of the hydrate reservoir can be more comprehensively captured, and the prediction precision of the hydrate saturation is improved. According to the combination, the complementary advantages of the two models, the simplicity of the two-parameter model and the physical basis of the equivalent medium model are utilized, so that the prediction result is more reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrate geophysical exploration, and in particular to a method and device for jointly predicting hydrate saturation based on dual parameters and equivalent media. Background Art

[0002] In the existing technology, the prediction of hydrate saturation mainly relies on a single parameter such as resistivity or acoustic wave time difference, which often cannot fully reflect the occurrence state of hydrate. Although the equivalent medium model takes into account the microscopic morphology of hydrate, it is complex to calculate in practical applications and it is difficult to quickly predict hydrate saturation. Summary of the invention

[0003] In order to solve the problems of insufficient accuracy, high computational complexity and failure to fully consider the occurrence state of hydrates in existing hydrate saturation prediction methods, the present invention provides a method and device for predicting hydrate saturation based on dual parameters and equivalent media to improve the accuracy and efficiency of prediction.

[0004] To achieve the above object, the technical solution of the present invention is: In a first aspect, the present invention provides a method for predicting hydrate saturation based on dual parameters and equivalent media, comprising: Acquire deep resistivity and acoustic transit time data of target hydrate reservoir areas; Using the deep resistivity and acoustic wave time difference data as input parameters of the dual-parameter model to obtain a predicted value of hydrate saturation of the dual-parameter model; The equivalent medium model is used to calculate the predicted value of hydrate saturation of the equivalent medium model; The weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value is obtained to obtain a final hydrate saturation prediction value.

[0005] Optionally, the two-parameter model is:

[0006] is the predicted value of hydrate saturation of the dual-parameter model, and are the baseline values ​​of deep resistivity and acoustic wave time difference, a and b are model coefficients; rt is the deep resistivity and ac acoustic wave time difference.

[0007] Optionally, the calculation method of using the equivalent medium model to calculate the predicted value of hydrate saturation of the equivalent medium model is: Bulk modulus of pore fluid for: ; in, is water saturation; and are the bulk moduli of water and hydrate, respectively; Hydrate saturation prediction value of equivalent medium model for:

[0008] Optionally, the weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value is performed to obtain the final hydrate saturation prediction value as follows:

[0009] is the final predicted hydrate saturation, and is the weight coefficient.

[0010] Optional, and The values ​​of are 0.32 and 0.68 respectively.

[0011] In a second aspect, the present invention provides a device for predicting hydrate saturation based on dual parameters and equivalent medium, comprising: A data acquisition module, used to acquire deep resistivity and acoustic transit time data of the target hydrate reservoir area; A dual-parameter model module, used to use the deep resistivity and acoustic wave time difference data as input parameters of the dual-parameter model to obtain a dual-parameter model hydrate saturation prediction value; An equivalent medium model module is used to calculate the predicted value of hydrate saturation of the equivalent medium model using the equivalent medium model; The weighted average module is used to perform weighted average on the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value to obtain a final hydrate saturation prediction value.

[0012] In a third aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; The processor is used to implement the steps of the method for predicting hydrate saturation based on dual parameters and equivalent media as described in any of the above items when executing the program stored in the memory.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention can more comprehensively capture the physical characteristics of hydrate reservoirs by combining the dual-parameter model (deep resistivity and acoustic transit time) with the equivalent medium model, thereby improving the prediction accuracy of hydrate saturation. This combination utilizes the complementary advantages of the two models, the simplicity of the dual-parameter model and the physical basis of the equivalent medium model, making the prediction results more reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flow chart of a method for predicting hydrate saturation based on dual parameters and equivalent media provided in an embodiment of the present application; Figure 2 This is a comparison chart of hydrate saturation prediction results calculated using different methods; Figure 3 A schematic diagram of the composition of a device for predicting hydrate saturation based on dual parameters and equivalent media provided in an embodiment of the present application; Figure 4 A schematic diagram of the composition of an electronic device provided in an embodiment of the present application; The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] Embodiment 1: Figure 1 A schematic diagram of a method for predicting hydrate saturation based on dual parameters and equivalent media provided in an embodiment of the present application. Figure 1 As shown, the method for predicting hydrate saturation based on dual parameters and equivalent medium provided in the embodiment of the present application may specifically include the following steps: Step 110, acquiring deep resistivity and acoustic wave transit time data of the target hydrate reservoir area; Step 120, using the deep resistivity and acoustic wave time difference data as input parameters of a dual parameter model to obtain a dual parameter model hydrate saturation prediction value; In this step, the hydrate saturation is predicted by combining two different logging parameters, deep resistivity and acoustic time difference. These two parameters reflect the influence of hydrate on resistivity and acoustic wave propagation velocity respectively. Through the established dual-parameter model, these two logging parameters, deep resistivity and acoustic time difference, are associated with hydrate saturation, thereby improving the accuracy of prediction, thus solving the problem of poor prediction accuracy of existing hydrate saturation predictions that mainly rely on single parameters such as resistivity or acoustic time difference. At the same time, since only two logging parameters are used, the calculation process is relatively simple and can quickly predict hydrate saturation.

[0018] Step 130, using the equivalent medium model to calculate and obtain a predicted value of hydrate saturation of the equivalent medium model; Step 140: performing weighted averaging on the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value to obtain a final hydrate saturation prediction value.

[0019] Since the dual-parameter model uses only two parameters, it may not be able to fully reflect the complex physical properties of the hydrate reservoir, especially when the hydrate distribution is uneven or the reservoir structure is complex, the prediction accuracy may be insufficient; in addition, since the accuracy of the dual-parameter model depends on the baseline values ​​of deep resistivity and acoustic time difference, if the baseline values ​​are inaccurate, the prediction results may be biased. To this end, this method can more comprehensively capture the physical properties of the hydrate reservoir by combining the dual-parameter model with the equivalent medium model, thereby improving the prediction accuracy of hydrate saturation. This combination utilizes the complementary advantages of the two models, the simplicity of the dual-parameter model and the physical basis of the equivalent medium model, making the prediction results more reliable.

[0020] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0021] Specifically, the two-parameter model is:

[0022] is the predicted value of hydrate saturation of the dual-parameter model, and are the baseline values ​​of deep resistivity and acoustic time difference, a and b are model coefficients; rt is deep resistivity, and ac is acoustic time difference.

[0023] In this way, the two parameters of deep resistivity and acoustic time difference can be associated with hydrate saturation through the dual-parameter model constructed above, thereby improving the accuracy of prediction. At the same time, the calculation process is relatively simple and can quickly predict hydrate saturation.

[0024] Specifically, the calculation method of using the equivalent medium model to calculate the predicted value of the hydrate saturation of the equivalent medium model is: Bulk modulus of pore fluid for:

[0025] in, is water saturation; and are the bulk moduli of water and hydrate, respectively; Hydrate saturation prediction value of equivalent medium model for:

[0026] In this way, through the above calculation method, the equivalent medium model can better describe the microscopic distribution and physical properties of hydrates in the reservoir, and can comprehensively capture the physical properties of the hydrate reservoir.

[0027] The weighted average of the hydrate saturation prediction value of the dual-parameter model and the hydrate saturation prediction value of the equivalent medium model is calculated as follows:

[0028] is the final predicted hydrate saturation, and are weight coefficients, which are 0.32 and 0.68 respectively.

[0029] The following is a further verification and explanation of this method in combination with an application scenario example: Take well logging as an example ( Figure 2), the red dashed line in the figure is the hydrate saturation prediction calculation result obtained by the dual-parameter model, the black dashed line is the hydrate saturation prediction calculation result obtained by the equivalent medium model, the blue line is the hydrate saturation prediction calculation result obtained by this method, and the green dots are the measured data of hydrate saturation. It can be seen that there are large differences between the hydrate saturation calculation results of the dual-parameter and equivalent medium models and the measured data, while the joint prediction results of this method are in good agreement with the measured results, and through fitting, and They are 0.32 and 0.68 respectively. This parameter can be applied to the calculation of hydrate saturation of other wells near the work area.

[0030] In summary, this method is based on rock physics theory, takes into account the influence of hydrates on resistivity and acoustic wave propagation velocity, as well as the microscopic distribution of hydrates in the reservoir, and has a scientific and reasonable theoretical basis. By combining the dual-parameter model (deep resistivity and acoustic wave transit time) with the equivalent medium model, this method can more comprehensively capture the physical properties of the hydrate reservoir, thereby improving the prediction accuracy of hydrate saturation. This combination utilizes the complementary advantages of the two models, the simplicity of the dual-parameter model and the physical basis of the equivalent medium model, making the prediction results more reliable.

[0031] Embodiment 2: See also Figure 3 As shown, the hydrate saturation prediction device 300 based on dual parameters and equivalent medium combined prediction provided in this embodiment mainly includes: A data acquisition module 310 is used to acquire deep resistivity and acoustic wave time difference data of a target hydrate reservoir region; A dual parameter model module 320 is used to use the deep resistivity and acoustic wave time difference data as input parameters of the dual parameter model to obtain a dual parameter model hydrate saturation prediction value; An equivalent medium model module 330 is used to calculate the equivalent medium model hydrate saturation prediction value using the equivalent medium model; The weighted average module 340 is used to perform weighted average on the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value to obtain a final hydrate saturation prediction value.

[0032] Specifically, the two-parameter model is:

[0033] is the predicted value of hydrate saturation of the dual-parameter model, and are the baseline values ​​of deep resistivity and acoustic time difference, respectively; a and b are model coefficients.

[0034] Specifically, the calculation method of using the equivalent medium model to calculate the predicted value of the hydrate saturation of the equivalent medium model is: Bulk modulus of pore fluid for:

[0035] in, is water saturation; and are the bulk moduli of water and hydrate, respectively; Hydrate saturation prediction value of equivalent medium model for:

[0036] Specifically, the weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value is calculated as follows:

[0037] is the final predicted hydrate saturation, and are weight coefficients, which are 0.32 and 0.68 respectively.

[0038] It should be noted that the device for predicting hydrate saturation based on dual parameters and equivalent media provided in the embodiment of the present application can execute the method for predicting hydrate saturation based on dual parameters and equivalent media provided in Example 1, and has the corresponding functions and beneficial effects of the execution method.

[0039] Embodiment 3: like Figure 4 As shown, an embodiment of the present application provides an electronic device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114; the memory 113 is used to store computer programs; the processor 111 is used to implement the steps of the method for jointly predicting hydrate saturation based on dual parameters and equivalent media provided in Example 1 when executing the program stored in the memory 113.

[0040] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A method for predicting hydrate saturation based on dual parameters and equivalent media, characterized in that: include: Acquire deep resistivity and acoustic transit time data of target hydrate reservoir areas; Using the deep resistivity and acoustic wave time difference data as input parameters of the dual-parameter model to obtain a predicted value of hydrate saturation of the dual-parameter model; The equivalent medium model is used to calculate the predicted value of hydrate saturation of the equivalent medium model; Taking a weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value to obtain a final hydrate saturation prediction value; The two-parameter model is: ； is the predicted value of hydrate saturation of the dual-parameter model, and are the baseline values ​​of deep resistivity and acoustic time difference, a and b are model coefficients, rt is deep resistivity, and ac is acoustic time difference.

2. The dual-parameter and equivalent medium combined prediction method for hydrate saturation according to claim 1 is characterized in that: The calculation method of using the equivalent medium model to calculate the predicted value of the hydrate saturation of the equivalent medium model is: Bulk modulus of pore fluid for: ; in, is water saturation; and are the bulk moduli of water and hydrate, respectively; Hydrate saturation prediction value of equivalent medium model for: .

3. The dual-parameter and equivalent medium combined prediction method for hydrate saturation according to claim 2 is characterized in that: The weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value is calculated as follows: ； is the final predicted hydrate saturation, and is the weight coefficient.

4. The dual-parameter and equivalent medium combined prediction method for hydrate saturation according to claim 3 is characterized in that: and The values ​​of are 0.32 and 0.68 respectively.

5. A device for predicting hydrate saturation based on dual parameters and equivalent medium, characterized in that: include: A data acquisition module, used to acquire deep resistivity and acoustic transit time data of the target hydrate reservoir area; A dual-parameter model module, used to use the deep resistivity and acoustic wave time difference data as input parameters of the dual-parameter model to obtain a dual-parameter model hydrate saturation prediction value; An equivalent medium model module is used to calculate the predicted value of hydrate saturation of the equivalent medium model using the equivalent medium model; A weighted average module, used to perform weighted average on the hydrate saturation prediction value of the dual-parameter model and the hydrate saturation prediction value of the equivalent medium model to obtain a final hydrate saturation prediction value; The two-parameter model is: ； is the predicted value of hydrate saturation of the dual-parameter model, and are the baseline values ​​of deep resistivity and acoustic time difference, a and b are model coefficients; rt is deep resistivity, and ac is acoustic time difference.

6. The device for predicting hydrate saturation based on dual parameters and equivalent medium combination according to claim 5, characterized in that: The calculation method of using the equivalent medium model to calculate the predicted value of the hydrate saturation of the equivalent medium model is: Bulk modulus of pore fluid for: ; in, is water saturation; and are the bulk moduli of water and hydrate, respectively; Hydrate saturation prediction value of equivalent medium model for: .

7. The device for predicting hydrate saturation based on dual parameters and equivalent medium combination according to claim 6, characterized in that: The weighted average of the dual-parameter model hydrate saturation prediction value and the equivalent medium model hydrate saturation prediction value is calculated as follows: ； is the final predicted hydrate saturation, and is the weight coefficient.

8. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the steps of the method for jointly predicting hydrate saturation based on dual parameters and equivalent media as described in any one of claims 1 to 4 when executing the program stored in the memory.

Images